John O Greene & Melanie Morgan. 21st Century Communication: A Reference Handbook. Editor: William F Eadie. Sage Publication. 2009.
Simple fact motivates this chapter: The mind makes including symbol systems (e.g., language), culture, and so on, that play a role in shaping and constituting communication events. Cognitive processes, though, are the absolutely essential and ineluctable foundation of communication—without these processes (which will be examined in this chapter), communication (whether it be interpersonal communication, intercultural communication, mass communication, whatever) simply doesn’t transpire.
“Cognition and information processing” is an umbrella term that encompasses all mental states and activities—those we are conscious of, those that take place outside of consciousness, and even consciousness itself. From the instant we encounter a stimulus to the time (a moment or years later) when we respond, cognitive processes are at work. Cognitive processes allow us to see, comprehend, move, and speak.
A Quick (and Selective) Survey of the Domain
To gain an appreciation of just how deeply intertwined cognitive processes and communication are, it is useful to consider some examples of the phenomena encompassed by “cognition and information processing.” To set the stage for that discussion, let us begin with a rudimentary scheme that partitions the mental realm into three components: the input-processing system, memory systems, and the output system.
Basic Frameworks of the Information-Processing System
The Input-Processing System
The input side of the information-processing system includes all those activities involved in taking in and making sense of the stimulus environment. The input-processing system thus includes processes such as attention, perception, and comprehension. The attentional subsystem functions to bring cognitive resources to bear in processing certain inputs, to the relative exclusion of others. In essence, attention is a selection system that serves as the “front door” to the rest of the information processing system: If you don’t attend to what another person is saying, or a message in the mass media, those inputs are not likely to have an impact.
Perception refers to a set of cognitive operations by which we segment and categorize stimulus inputs into meaningful relationships and kinds. For example, the perceptual subsystem allows us to recognize that some objects in our visual field are farther away than others, to identify the letters printed on this page, to isolate the sound units that make up spoken language, and to recognize facial expressions of emotion. Our perceptual systems allow us to arrive at a coherent, “sensible” grasp of what’s out there. Take away perceptual systems, and the world becomes a morass of unintelligible shapes, colors, movement, and sound.
Comprehension encompasses those processes by which we combine basic perceptual information with knowledge of causal relationships, rules of language, social regularities, and so on to construct a model of unfolding reality. For example, it is comprehension processes that permit us to move from the perception of linguistic sound units to an understanding of the meaning of a phrase (e.g., “You look so handsome tonight.”); to link successive utterances, even when there is no stated connection between them (“And you must have been drinking.”); and to make sense of those phrases as elements of a larger discourse or story (“That’s it; I’m going home to mother!”).
The Memory System
The memory system can be partitioned in various ways, but doubtless the most fundamental distinction is between long-term memory (LTM) and short-term, or working, memory (STM). As the label suggests, LTM is a repository that preserves information for an extended period—even years or decades. Moreover, the capacity of LTM is virtually unlimited—we don’t have to forget old information in order to make room for new facts. Again, there are different ways of subdividing the LTM system, but one common approach distinguishes between declarative and procedural memory. Declarative memory is memory for facts—the things you know about the world. It is in declarative memory that you have retained your mother’s middle name, the story line of No Country for Old Men, and the lyrics of your favorite songs. Procedural memory, on the other hand, contains information about how to do things: It is the basis of our skills. Because of procedural memory, people are able to drive a car, pronounce the words of their native language, or play a musical instrument.
While LTM preserves a vast store of information, most of that information isn’t available for use or processing at any particular time—cognitive scientists say that it isn’t “activated.” The STM system, then, is the site of information that is activated and available for further processing. You could think of LTM as a blackboard filled with written statements in a darkened room and STM as a small portion of that information illuminated by the beam of a flashlight. As the light beam moves across the board, information is lost from the STM as new facts enter. So, unlike LTM, where the storage capacity is virtually unlimited and where information is preserved perhaps for a lifetime, STM holds a very limited amount of information and for only a brief period. On the other hand, STM allows you to rehearse, manipulate, and elaborate its contents: You can, for example, rehearse a new acquaintance’s telephone number, add its digits, or even mentally traverse them in reverse.
The Output System
The output side of the information-processing system involves all those processes by which we formulate and execute behavioral responses. Essential components include, but aren’t limited to, activities such as those identified in the goals-plans-action (G-P-A) model (Dillard, 2008): goal formation, response planning, and the assembly and implementation of overt behaviors. Scholars differ in their conception of the exact nature of “goals” (e.g., must they be conscious?), but the basic notion of what goals are is one we all intuitively grasp: Goals define what we’re trying to accomplish and constrain how we go about it (e.g., the car salesperson tries to make a sale without appearing to be too aggressive). Goal-formation processes, then, are those that give rise to these objectives and constraints. As the “drivers” of the output system, goals channel mental resources toward particular cognitive activities and thereby shape how and what we think, and what we do and how we go about it.
Planning involves formulating a behavior, or more likely a sequence of behaviors, for accomplishing one’s goal(s), and it entails several distinct subprocesses (see Berger, 1997). For example, one aspect of planning is the identification of subgoals—intermediate steps that must be taken to achieve the overarching objective (e.g., to accomplish the goal of serving dinner, one must procure the necessary ingredients, combine them properly, preheat the oven, etc.). Planning also involves identifying potential ways of accomplishing each goal or subgoal (e.g., given the goal of introducing himself to a stranger, a certain denizen of the jungle might consider saying “Hello, my name is Tarzan, and I am delighted to make your acquaintance” or, alternatively, “Me Tarzan.”). And yet a third component of planning is anticipating the likely outcomes of potential behaviors, that is, “engaging in Behavior X is likely to result in Outcome Y.”
Assembling and implementing behaviors involves those processes by which our plans are actually manifested as overt responses (see Greene, 2007). The content of plans is represented in relatively abstract mental formats—the sorts of symbolically based representational formats of which we are consciously aware and that we can even report or describe to others (so, e.g., you can tell your roommate what you’re planning to do over the weekend). On the other hand, overt behavior consists of the motor commands that allow us to speak and move. There is an intricate system that translates our conscious conceptions of what to do into actual behavior, and without this component of the output system, we might possibly still be thinkers (of a sort), but we couldn’t be doers.
A “Second Tier”: Building on a Basic Framework
The preceding section should make it pretty clear that the input-processing, memory, and output systems play an inescapable role in communication processes. But for communication scientists, the properties of these systems are typically not so much a primary focus as they are an essential foundation for exploring a vast array of phenomena that derive from and are shaped by the nature of these systems. It is instructive, then, to consider a few examples of these “second-tier” phenomena.
Among the most common conceptions in cognitive science is the notion that the mind is a limited-capacity system in the sense that there is a finite pool of “processing resources” that restricts the number of mental activities we can carry out at any given time. If some activity makes heavy demands on our processing resources, we are said to be under a heavy “cognitive load,” and our ability to carry out other activities is curtailed. So, for example, if you are engrossed in text-messaging your roommate, you probably aren’t going to be able to process what your professor is saying about some complex topic. This idea of a limited-capacity system shows up in a variety of communication phenomena. For example, while it is not always true, everything else being equal, lying tends to be more cognitively demanding than telling the truth: The liar has to fabricate an account, keep his or her story straight, control nonverbal behaviors so as not to give himself or herself away, and so on. As a result, liars often exhibit behaviors indicative of heavy cognitive load (e.g., speech errors). A second example, often in the news these days, comes from studies that show that hands-free cell phones are no safer when driving than hand-held models. The reason, of course, is that it’s not having something in your hand that creates the problem; rather, the problem stems from having something other than monitoring the road on your mind.
Communication Skill Acquisition
It will come as no surprise to the readers of this volume that communication skills matter—skillful communicators simply fare better in the workplace and in their interpersonal relationships (e.g., marriages). But people aren’t born with communication skills; they are acquired over time, through practice. The process of skill acquisition is accompanied by a number of behavioral changes; for example, we get faster, we make fewer errors, and we experience less cognitive load. Cognitive science has made considerable strides in illuminating what happens in the mind as we acquire a skill and why these behavioral changes occur (see Greene, 2003). For example, recalling the declarative versus procedural memory distinction described above, one of the things thought to happen in skill acquisition is that one may learn a set of facts about what to do, and through practice, gradually convert this declarative knowledge into procedural form so that it is no longer necessary to keep the rules about what to do in mind.
There is another layer to the advances that have come from studies of skill acquisition. Because research has shed light on what happens in the mind as we acquire a skill, we can take that understanding and use it to design more effective training programs. For example, what are the most effective ways of instructing people about the skill, what conditions of practice are most effective, and what sorts of feedback are best for learning and skill transfer?
Creativity and Pattern
Human behavior is characterized by regularity and pattern. We readily recognize this in the behavior of others (and sometimes in ourselves). Our friends and loved ones have ways of speaking (e.g., favorite topics, vocabulary) and moving (e.g., facial expressions, mannerisms) that are just “them.” And the patterning of human behavior doesn’t just show up in individuals’ idiosyncratic ways of doing things. Members of groups (e.g., sorority members; church congregations), and even entire cultures, exhibit routines in their behavior that are common to all members of the group. We all know, for example, the basics of what to say and do when being introduced to someone.
Because this patterned, repetitive character of human behavior is so universal and so ubiquitous, failing to address it would leave some pretty big gaps in our understanding of communication processes. This is precisely one of the places, though, where cognitive science has made some important inroads. The fact that there is a repetitive element to our behavior implicates LTM. In other words, people must have preserved (in some form) the information used to produce the patterns they exhibit. Guided by this assumption, cognitive scientists have learned a lot about the nature of the LTM system(s), where knowledge of behavioral routines is represented, how that knowledge is acquired, and how it is used in shaping our actions (see Kellermann & Lim, 2008).
What is particularly fascinating in the context of a discussion of the patterned and repetitive nature of human behavior is that it is also simultaneously unique and creative. Sure, we exhibit idiosyncratic and shared ways of doing things, but we never do them in exactly the same way from one time to another. It turns out, for example, that even if you tried to repeat even a simple phrase three times in a row in exactly the same way, there would be variations in the vocal spectrograph of each repetition. Even more important, we have the capacity to think and say new things—to come up with ideas that we’ve never heard, seen, or thought before. This penchant for creation is the source of much of the best in human communication—our ability to tell a compelling story, to express an idea or feeling in just the right words, and even to come up with a great joke. As you might guess, studying and understanding the creative side of communication behavior is more difficult than coming to grips with the patterned aspects, but even here, theoretical and methodological advances have been made (see Greene, 2008).
Self and Self-Regulation
Like no other species, human beings have the ability to reflect on themselves—we are self-aware; we possess conceptions of who we “are” (and who we wish we were); and we think of ourselves and our actions in relation to others and their perceptions, actions, and purposes. These and related self-relevant phenomena are central to social interaction. Such processes have been shown to be linked to social motivation (including concerns with self-presentation), social anxiety, marital satisfaction, and attitude—behavior relationships, to list just a few out of many.
Because they are mental phenomena, self-concept, self-regulation, and so on fall squarely in the domain of cognitive science, and considerable progress has been made in understanding their nature (see Baumeister, 1998). For example, one property of our experience of self is that it is relatively stable—we have a sense of unity and continuity concerning who we are. When I wake up in the morning, I feel that I am essentially the same person I was the day before. On the other hand, it turns out to be fairly easy to demonstrate that people’s conceptions of their abilities, attributes, and so on are often internally inconsistent and also malleable and subject to change. Models that describe the way self-relevant information is stored in and retrieved from LTM help explain how we can entertain inconsistent views of ourselves; how those perceptions of self can shift, sometimes pretty rapidly; and how even in the face of such inconsistency and change, we are able to maintain a coherent sense of self.
As a second example, while the self very often plays a role in motivating and shaping one’s behavior, this is not always true: There are times when we are not conscious of our selves (our thoughts, behavior, etc.). Models of self-awareness have shed light on those conditions under which aspects of the self are more or less likely to come into play, as well as on the behavioral consequences of self-awareness (see Baumeister, 1998).
Cognitive Changes over the Life Span
Among the most intensively studied aspects of cognitive functioning are the various changes in mental processes that occur over the course of a person’s life. As we grow from infancy to childhood, adolescence, and beyond, numerous developments take place in the input-processing, memory, and output systems. For example, cognitive processes simply get faster over the course of childhood, we acquire the capacity to think in more abstract ways, and we develop the ability to monitor and regulate our own behavior.
Some of the cognitive changes accompanying development are particularly relevant to communication and social interaction. These include language acquisition, which typically commences with the production of single words around the end of the first year and rapidly progresses to multiple-word strings by about 18 months (see Clark, 2003). A second example of a socially relevant developmental change during childhood concerns what is termed the “theory of mind,” or the understanding that other people possess knowledge, beliefs, goals, and so on and that these may differ from one’s own mental states (see Premack & Premack, 2003). In the same vein, as children develop the ability to take the perspective of others, they also begin to engage in strategic self-presentation in order to manipulate what others think of them (e.g., Aloise-Young, 1993).
The other end-of-the-life course is marked by cognitive changes as well. The efficiency of mental processing peaks as we reach early adulthood but begins a gradual decline shortly thereafter. An overall slowing of information processing begins in the early 20s. This decline becomes more pronounced as we age, ultimately affecting the ability to process language and text. Evidence of this decay is apparent in the communication patterns used by older adults, which can often be characterized as less complex (e.g., shorter, grammatically simpler constructions; fewer personal pronouns) than those exhibited by their younger counterparts (Kemper, 2006). As we age, we also experience deterioration in the efficiency of the attentional subsystem. We become less proficient in our ability to inhibit irrelevant stimuli (e.g., extraneous thoughts), making it more difficult to be attuned to important message features. Older adulthood affects memory as well. Decreases in STM begin in the 20s and become more pronounced with each passing decade—a deficit directly related to difficulty in sentence processing. With respect to the LTM system, declarative memory is negatively affected by age, but procedural memory is relatively impervious to the aging process. So while you may forget the name of your childhood best friend, you won’t forget how to play the piano.
A Second Pass at the “Second Tier”
The phenomena we’ve considered to this point, cognitive load, skill acquisition, creativity, the self, and life span changes, are simply examples, albeit fascinating examples, of what we’ve termed “second-tier” cognitive processes. There are many other such phenomena, and we should at least mention some of those that we could have as easily selected for inclusion here: cultural differences and similarities in information processing, the role of gender in thought and action, aesthetics and the perception of order and beauty, second-language acquisition, verbal and nonverbal message production (including understanding the link between the two), imagined interactions, person perception and impression formation, stereotyping and prejudice, attitudes (and the link between attitudes and behavior), self-deception, reasoning and decision making, consciousness, motivation, and emotion.
The Methods of Cognitive Science
The overview of the input-processing, memory, and output systems in the preceding section should make it obvious that no matter what communication phenomenon one sets out to understand, sooner or later, dedicated pursuit of that phenomenon leads to the realm of the mind. It is possible, of course, to skirt the boundaries of the mental realm, assuming or ascribing properties (warranted or not) to the ultimate seat of message making and message processing (just as the early mapmakers designated the locations of “Atlantis” and “dragons”). Cognitivists, though, tend to be the sort of thinkers who want to know what’s there. And just as explorers during the Age of Discovery developed new tools and techniques for exploring the terrestrial realm (and those of our age, the celestial), cognitive scientists are able to draw on an array of innovative methods for understanding the nature of the mind. These techniques are both varied and numerous, but among the most important are verbal reports, memory assessments, temporal measures, and examination of performance errors.
Doubtless the most obvious and straightforward way of gaining insight into what and how people are thinking is to ask them. Under certain conditions, for example, people might reasonably be expected to be able, and willing, to tell you what they are trying to accomplish and how they are planning to go about it. Such verbal reports, however, can take numerous forms, and some are more or less reliable and valid than others (see Ericsson & Simon, 1996). For example, asking people to report on their activities and motivations is often problematic because they may censor or alter their accounts due to concerns associated with social appropriateness or out of considerations about what the investigator “wants to hear.” Even framing a verbal report as an instance of “communication” can shift the content of what is said from “that which one is thinking” to “that which would be sensible to the listener.”
In addition to the various social constraints on the content and quality of verbal reports, cognitive factors also pertain. For example, evidence suggests that people are more likely to give accurate reports of current thoughts and activities as opposed to retrospective accounts. Similarly, when people are asked about whether certain events or stimuli (e.g., an advertisement) may have influenced their behavior, they may quite easily answer the question not by relying on any specific or accurate memory of that influence but rather by inferring a plausible link (e.g., “I must have seen the ad, and I’m almost certain I bought the product, therefore I distinctly remember being influenced by that ad.”).
Finally, as a way of shedding light on cognitive processes, the usefulness of verbal reports is limited by the fact that many mental processes simply aren’t available to conscious awareness. You are aware, for example, of the words on this printed page, but not of the cognitive operations that allow you to perceive them; you apprehend the contents of your own consciousness at this instant, and maybe, if you direct your thoughts deeper, even of the environmental stimuli and remembered events that contribute to the thought(s) in your mind at this moment. But chase as you will, you can only capture the content and residue of your thoughts and not the processes by which they came to be.
As noted in the first section of this chapter, the memory system holds a central place in science’s understanding of mental processes. It should be no surprise, then, that a great deal of effort has been devoted to exploring the nature of memory and various memory phenomena (see Tulving & Craik, 2000). In the main, studies of LTM involve either recognition or recall paradigms. Recognition studies typically involve two phases: In the first, people are presented with a series of stimuli (e.g., magazine ads), and in the second phase, the original stimuli are presented along with new stimuli of the same type. Participants, then, are asked to judge whether each item is “old” or “new.” Recall studies, in contrast, simply ask respondents to produce previously encountered information (e.g., “What is the capital of New York?”). The distinction between recognition and recall studies is exemplified in the difference between multiple-choice tests (which involve recognition) and short-answer or fill-in-the-blank exams (which require recall), and as you might expect, people tend to perform better on recognition tasks than on recall tasks. However, what is remarkable is that there are certain conditions under which that tendency is reversed, where people can actually recall information that they cannot recognize.
One of the key understandings to emerge from the research on memory processes is that memory is fundamentally a constructive process. In other words, memory doesn’t work like pulling up an intact document file stored on your computer. Instead (completely out of conscious awareness), multiple (incomplete) memory traces are retrieved, combined with current environmental stimuli, and laid over with sense-making cognitive processes to create a “recollection” of what transpired at some point in the past. Neath and Surprenant (2003) report an interesting example of this sort of memory construction involving a student who had fond childhood memories of a beloved family dog. As real as this memory was for this young woman, it turned out that the dog had died 2 years before she was born! This same sort of memory construction has been shown to apply in cases of eye-witness testimony, which is notoriously inaccurate, even under oath and, literally, with life-or-death decisions at stake (see Loftus, 1996). And that’s not the end of it: So pervasive is the constructive nature of recall that it occurs even to those “crystallized” moments that seem so indelibly etched in our minds that we would never forget them. For example, Talarico and Rubin (2003) found that in less than 1 year, people’s recollection of the events of September 11, 2001, were just as subject to loss and error as their memories of everyday occurrences.
Beyond our (in)ability to remember the events of our lives, other memory phenomena are equally compelling. For example, one line of research has examined people’s ability to remember visual versus textual information (see David, 2008). This work shows that we tend to have better memory for pictures than text, and this effect extends even to printed words that have visual referents (e.g., “mountain”) versus those that are more abstract (e.g., “freedom”). Other studies have examined our ability to remember messages, both from face-to-face interactions and from the media (e.g., news reports, movies). Among the interesting findings of these studies is that we tend to have better memory for “what the other person said” in an interaction than what “we said” and that we are much better at recalling the “gist” of a conversation or story than the specific words that were used in its telling.
One final example of what we’ve learned about memory processes will resonate if you’ve ever observed that your ability to remember class material is worse on the final exam or your recall of jokes is better in bars. It turns out that our ability to retrieve information from memory is better when the conditions at the time of recall are similar to those at the time we originally acquired that information. So if your class meets in one room all semester and then you take the final in a different room, your ability to recall course material is reduced. And the same effect applies to your physiological state: If you study while drinking coffee, you’ll have better recall with some caffeine in your system. Similarly, if you learn all your best jokes while drinking beer in campus bars, you’re more likely to remember those jokes when you’re in that same state and environment. This effect is so strong that people who are given the task of learning word lists underwater in scuba gear have better recall of those words when they’re back underwater than when they’re on dry land (see Neath & Surprenant, 2003).
Since the very inception of the scientific study of the mind almost 150 years ago, scholars have relied on measures of time to draw conclusions about the nature of mental processes. There are several, interrelated reasons that time is one of the most important tools of the cognitive scientist. Most simply, cognitive processes, like all other processes (e.g., boiling an egg, a solar eclipse) transpire over time, and for that reason, one of the key elements of understanding how a process works is to know how long it takes. By extension, assessing time allows one to determine whether a process takes longer under some conditions than others: If you have a good grasp of how something is operating, then you should be able to predict what factors will cause it to speed up or slow down (e.g., lowering the temperature will cause a chemical reaction to proceed more slowly). A third consideration is that examining the temporal characteristics of cognitive processes applies even to phenomena that occur outside of conscious awareness and thus are not available for verbal report. A final reason why temporal measures play such an important role in cognitive science stems from the notion of “cognitive load” discussed previously. When mental activities make heavy demands on our finite pool of processing resources, our ability to carry out those activities is often slowed. For this reason, then, measures of response time can be used to draw conclusions about the cognitive demand that a person is experiencing.
Temporal assessments involve a variety of methodologies, depending on the specific aspect of the mental system that is under examination, but they typically involve measuring the time between presentation of some stimulus or task and initiation (or completion) of a subsequent response. The instructions can be as simple as pressing a button when a sound occurs or as complex as solving calculus problems. As a result of their versatility, temporal measures are commonly used to study each of the three major systems of the mind (input processing, memory, and output). In the input-processing realm, for example, studies indicate why some visual images take longer to be recognized than others (perception) and why it sometimes takes a while to comprehend a message (as when it takes us a few seconds to “get a joke”). With respect to memory, any number of experiments have shed light on conditions under which it takes us longer to retrieve information from LTM (the sort of occurrence that will resonate if you’ve ever “forgotten” your own phone number, experienced the “tip-of-the-tongue phenomenon,” or momentarily blanked on the name of a person whom you know well).
One additional group of temporal measures merits special mention because they are directly tied to communication processes. Consider that verbal message production is characterized by various temporal parameters including speech rate (e.g., words per minute), speaker-turn latency (the period between when one person stops talking and another begins), and pause-phonation ratio (the duration of periods of silence divided by the duration of periods of talk during a person’s speaking turn). These sorts of variables are particularly interesting because they lead “dual lives”: On the one hand they have social significance because they are related to perceptions of credibility, social attractiveness, and so on, and on the other, they provide a window on the cognitive processes underlying speech production. Research on these temporal parameters shows that we speak more fluently (i.e., quickly, with less silent pausing) when we are familiar with our topic and when we’ve had an opportunity to plan what we’re going to say in advance. Conversely, multiple-goal messages (e.g., trying to tell a friend that you didn’t think much of her American Idol audition while also trying to be supportive) tend to slow us down.
The final type of assessment in the cognitivist’s toolkit actually goes hand in hand with those we’ve already covered. Studies that involve temporal measures also almost always examine errors in what a person says and does. This is because most tasks involve a speed-accuracy trade-off: The quicker we act, the more errors we tend to make. (So you don’t want to rush through an exam, and you really don’t want your surgeon to be in too big a hurry!) Moreover, as we’ve alluded, in their verbal reports and in their memory performance, people make errors. What is particularly useful, though, is that when we do commit these errors, they are not random glitches—they emerge under certain conditions and not others; they are of certain types and not others. For example, people tend to “recall” events that never happened if those unseen occurrences are part of a “script,” or a familiar sequence of events. Similarly, we tend to “run off” well-practiced behavioral routines, even when they are not appropriate—and you have experienced this if you’ve ever called a new beau by the last one’s name or, less embarrassingly, moved and found yourself dialing your old telephone number or even “driving home” to your old address! The key point is that because performance errors exhibit regularity rather than randomness, they provide an important window on the operation of the mind, not just when it “fails” but also when it is functioning normally.
The Special Allure of Cognitivism
The overarching theme of this chapter has been that cognitive processes lie at the very heart of human communication: The mind is the seat of message making and message comprehension. You can take away any other aspect of human existence (language, relationships, culture, cell phones, iPods, …—you fill in the blanks) and still have communication, but without the mind, you’ve got nothing. By extension, whatever other communication phenomenon one seeks to understand, sooner or later, pursuit of that issue will lead you to confront the nature of comprehension and action.
But the central and inescapable role of cognition in communication is only one of the reasons why cognitivism has come, here in the dawning years of the 21st century, to hold the position it does among all the various alternative approaches for studying communication processes. If the two of us, as your authors, have done any sort of creditable job to this point, a second contributing factor should be readily apparent: The phenomena in cognitivism’s wheel-house are inherently fascinating. As much as humans wonder at the complexity of the galaxies and the intricate nature of Earth’s ecosystems, when God spoke these things into being, He was only getting warmed up, and He saved His best for last. The phenomena of the mind are intrinsically compelling: What is consciousness? How is it possible to think and do something new? What is the nature of dreams (and daydreaming)? How does what I think become manifested as speech and movement? How is it possible to know what to do, and to want to do it, and still do something else? How can I be so certain in my recollections—and so wrong? Why can’t some people dance without looking at their feet?
Beyond the essential place of cognition in communication and the fascinating nature of the phenomena that it encompasses, there is yet a third reason (a whole cluster of reasons, actually) that gives cognitivism its particular appeal, and this is that it allows us to have our cake and eat it too. By this, we mean that people are sometimes led to think in terms of trade-offs and dichotomies (you can have one or the other), but the special nature of cognitivism allows one to work simultaneously at both “ends” of some commonly supposed continua. Let’s consider three examples that illustrate this point.
Science and Aesthetics
One of the peculiar properties of human sense making is that we are so very prone to error and bias in what we perceive and suppose about the world. We see order, regularity, and association where it doesn’t exist, and conversely, we fail to detect processes that really are at work. As an approach to understanding, science functions to minimize such error (see Haack, 1999). Rather than accept an assertion on faith or because someone in authority says it is so, science ultimately hinges on publicly available and replicable methods and data; it employs rigorous techniques to reduce the chances of illusion and the impact of wishing it were so.
At the same time that cognitivism affords the special advantages of science as a way of knowing, it also resonates with our aesthetic nature and our appreciation of order and beauty. And this is true in two distinct senses that are analogous to the ways in which a work of art can function aesthetically. A still life of a flower arrangement, for example, could reveal the beauty and structure of the blossoms, and at another level, that same painting can be appreciated for the artist’s technique. In much the same way, the data and models of cognitive science reveal an elegance and order in human behavior that we might not apprehend otherwise. And at another level, the theories and models of cognitive science can, themselves, be a source of pleasure and satisfaction.
Theory and Practical Application
As we have just noted, thinking theoretically can be a source of genuine pleasure and excitement. People enjoy working on Sudoku and crossword puzzles, but building scientific theories is like working out newspaper puzzles on steroids. Theory construction is problem solving—finding ways of making sense of patterns of regularities and anomalies, and it requires imagination, intellectual discipline, and courage. And the appeal of thinking theoretically doesn’t pertain just to building one’s own theories; investing the effort to master the theories of others helps us to appreciate the “big picture” of how things fit together and why they work as they do, to understand how someone else went about trying to solve a problem, and even to think about things that person didn’t see.
The sense of insight and satisfaction that comes from thinking theoretically is only half the story here because, even though cognitivism is fundamentally theory driven, the problems addressed by cognitive science are those that have very real applications and implications for people’s lives. Just a few examples should be sufficient to illustrate the point: How can children with learning disabilities best acquire social skills; how can the cognitive changes that occur with advancing age be delayed or accommodated; and how can health campaign messages (e.g., don’t drink during pregnancy). be designed to enhance the likelihood that people will attend, comprehend, and implement their recommendations? The overarching point is that if you want to make a difference in the quality of people’s lives, it helps to understand how, and what, they think.
Universality and Difference
Cognitive science seeks to develop models of mental processes that are general in the sense that they apply to everyone. As an example, consider that people integrate sensory inputs with information in LTM in a way that allows them to understand the dialogue and follow the storyline of a movie. The cognitive theorist, then, sets out to develop an account of how this happens in a way that applies to all people (and all movies), not unlike the way physicists attempt to articulate the laws that govern the motion of all objects.
At the same time that congnitivism seeks to develop powerful, general accounts, it also seeks to understand the source and nature of differences in the way people process information and generate responses. Are there, for example, cultural differences in the content and structure of information in the LTM that are manifested in perception, comprehension, recall, and speech and action? At an individual level, why do experts in a particular domain perceive and interpret domainrelevant stimuli differently than do novices?
This striving after both universality and difference is illustrated in work that your authors have conducted on creativity in thought and behavior over the last half-dozen years. As we noted earlier in this chapter, human action is inherently creative—we all do it, and so part of our project has been to understand how it is possible for us to think and say new things (see Greene, 2008). On the other hand, some people just seem better at it than others: We all know people who just seem to be able to “think on their feet,” and we’ve been exploring what is at the root of this individual difference (see Morgan, Greene, Gill, & McCullough, in press).
Communication’s Place in Cognitive Science: The Interplay of Minds
Cognitive science is an enormously broad interdisciplinary enterprise that spans a great many traditional fields of inquiry. Without any effort to formulate a comprehensive list, we can say that cognitive science draws on philosophy, neuroscience, anthropology, sociology, psychology, linguistics, computer science, mathematics, … and communication. One of the great freedoms afforded by cognitivism is that of pursuing one’s questions wherever they may lead. Rather than stopping or changing course because what one is doing is “not communication,” the cognitivist can go where he or she will.
At the same time, communication’s emphasis on message behavior, code systems, social relationships, channel effects, and so on puts scholars in the field in a position to make unique contributions to cognitive science. A particularly interesting example involves the study of mutual influence processes—the ways in which the behaviors of interactants unfold in interdependent ways (see Burgoon, Stern, & Dillman, 1995). While much of the history of cognitivism has focused on studying the mind of the individual engaged in various tasks, there is a growing emphasis on exploring the interplay of minds (whether it be face to face, online, etc.). Communication scholars have much to contribute to that conversation.